Safety and Efficacy of a Dapivirine Vaginal Ring for HIV Prevention in Women.

BACKGROUND: The incidence of human immunodeficiency virus (HIV) infection remains high among women in sub-Saharan Africa. We evaluated the safety and efficacy of extended use of a vaginal ring containing dapivirine for the prevention of HIV infection in 1959 healthy, sexually active women, 18 to 45 years of age, from seven communities in South Africa and Uganda. METHODS: In this randomized, double-blind, placebo-controlled, phase 3 trial, we randomly assigned participants in a 2:1 ratio to receive vaginal rings containing either 25 mg of dapivirine or placebo. Participants inserted the rings themselves every 4 weeks for up to 24 months. The primary efficacy end point was the rate of HIV type 1 (HIV-1) seroconversion. RESULTS: A total of 77 participants in the dapivirine group underwent HIV-1 seroconversion during 1888 person-years of follow-up (4.1 seroconversions per 100 person-years), as compared with 56 in the placebo group who underwent HIV-1 seroconversion during 917 person-years of follow-up (6.1 seroconversions per 100 person-years). The incidence of HIV-1 infection was 31% lower in the dapivirine group than in the placebo group (hazard ratio, 0.69; 95% confidence interval [CI], 0.49 to 0.99; P=0.04). There was no significant difference in efficacy of the dapivirine ring among women older than 21 years of age (hazard ratio for infection, 0.63; 95% CI, 0.41 to 0.97) and those 21 years of age or younger (hazard ratio, 0.85; 95% CI, 0.45 to 1.60; P=0.43 for treatment-by-age interaction). Among participants with HIV-1 infection, nonnucleoside reverse-transcriptase inhibitor resistance mutations were detected in 14 of 77 participants in the dapivirine group (18.2%) and in 9 of 56 (16.1%) in the placebo group. Serious adverse events occurred more often in the dapivirine group (in 38 participants [2.9%]) than in the placebo group (in 6 [0.9%]). However, no clear pattern was identified. CONCLUSIONS: Among women in sub-Saharan Africa, the dapivirine ring was not associated with any safety concerns and was associated with a rate of acquisition of HIV-1 infection that was lower than the rate with placebo. (Funded by the International Partnership for Microbicides; ClinicalTrials.gov number, NCT01539226 .)

Marginal correlation from an extended random-effects model for repeated and overdispersed counts

Vangeneugden et al. [15] derived approximate correlation functions for longitudinal sequences of general data type, Gaussian and non-Gaussian, based on generalized linear mixed-effects models (GLMM). Their focus was on binary sequences, as well as on a combination of binary and Gaussian sequences. Here, we focus on the specific case of repeated count data, important in two respects. First, we employ the model proposed by Molenberghs et al. [13], which generalizes at the same time the Poisson-normal GLMM and the conventional overdispersion models, in particular the negative-binomial model. The model flexibly accommodates data hierarchies, intra-sequence correlation, and overdispersion. Second, means, variances, and joint probabilities can be expressed in closed form, allowing for exact intra-sequence correlation expressions. Next to the general situation, some important special cases such as exchangeable clustered outcomes are considered, producing insightful expressions. The closed-form expressions are contrasted with the generic approximate expressions of Vangeneugden et al. [15]. Data from an epileptic-seizures trial are analyzed and correlation functions derived. It is shown that the proposed extension strongly outperforms the classical GLMM.

Selection models and pattern-mixture models to analyze longitudinal quality of life data subject to dropout.

SUMMARY Longitudinally observed quality of life data with large amounts of drop-out are analysed. First we used the selection modelling framework, frequently used with incomplete studies. An alternative method consists of using pattern-mixture models. These are also straightforward to implement, but result in a di erent set of parameters for the measurement and drop-out mechanisms. Since selection models and pattern-mixture models are based upon di erent factorizations of the joint distribution of measurement and drop-out mechanisms, comparing both models concerning, for example, treatment e ect, is a useful form of a sensitivity analysis

Validation of Surrogate Markers in Multiple Randomized Clinical Trials with Repeated Measurements

Part of the recent literature on the validation of biomarkers as surrogate endpoints proposes to undertake the validation exercise in a multi-trial context which led to a definition of validity in terms of the quality of both trial level and individual level association between the surrogate and the true endpoints (BUYSE et al., 2000). These authors concentrated on continuous univariate responses. However, in many randomized clinical studies, repeated measurements are encountered on either or both endpoints. When both the surrogate and true endpoints are measured repeatedly over time, one is confronted with the modelling of bivariate longitudinal data. In this work, we show how such a joint model can be implemented in the context of surrogate marker validation. In addition, another challenge in this setting is the formulation of a simple and meaningful concept of "surrogacy". We propose the use of a new measure, the so-called variance reduction factor, to evaluate surrogacy at the trial and individual level. On the other hand, most of the work published in this area assume that only one potential surrogate is going to be evaluated. We also show that this concept will let us evaluate surrogacy when more than one surrogate variable is available for the analysis. The methodology is illustrated on data from a meta-analysis of five clinical trials comparing antipsychotic agents for the treatment of chronic schizophrenia

Coping With Memory Effect and Serial Correlation When Estimating Reliability in a Longitudinal Framework

Longitudinal studies are permeating clinical trials in psychiatry. Therefore, it is of utmost importance to study the psychometric properties of rating scales, frequently used in these trials, within a longitudinal framework. However, intrasubject serial correlation and memory effects are problematic issues often encountered in longitudinal data. In the present work the authors study, via simulation, the impact of uncontrolled sources of serial correlation on newly proposed measures, designed to evaluate reliability in a longitudinal scenario. This study also addresses the relationship between serial correlation and memory effect. The simulations illustrate that ignoring serial correlation can have a severe impact on the estimates of reliability and on inferences related to it. Importantly, the authors show that the underlying modeling framework used in this new approach allows correcting for this type of correlation and avoiding bias. Moreover, it can adjust for the presence of a memory effect. Nevertheless, to achieve that, a careful model building is required. © The Author(s) 2010.status: publishe

Validation of a longitudinally measured surrogate marker for a time-to-event endpoint

The objective of this paper is to extend the surrogate endpoint validation methodology proposed by Buyse et al. (2000) to the case of a longitudinally measured surrogate marker when the endpoint of interest is time to some key clinical event. A joint model for longitudinal and event time data is required. To this end, the model formulation of Henderson et al. (2000) is adopted. The methodology is applied to a set of two randomized clinical trials in advanced prostate cancer to evaluate the usefulness of prostate-specific antigen (PSA) level as a surrogate for survival.

Simulation-guided phase 3 trial design to evaluate vaccine effectiveness to prevent Ebola virus disease infection: Statistical considerations, design rationale, and challenges.

Starting in December 2013, West Africa was overwhelmed with the deadliest outbreak of Ebola virus known to date, resulting in more than 27,500 cases and 11,000 deaths. In response to the epidemic, development of a heterologous prime-boost vaccine regimen was accelerated and involved preparation of a phase 3 effectiveness study. While individually randomized controlled trials are widely acknowledged as the gold standard for demonstrating the efficacy of a candidate vaccine, there was considerable debate on the ethical appropriateness of these designs in the context of an epidemic. A suitable phase 3 trial must convincingly ensure unbiased evaluation with sufficient statistical power. In addition, efficient evaluation of a vaccine candidate is required so that an effective vaccine can be immediately disseminated. This manuscript aims to present the statistical and modeling considerations, design rationale and challenges encountered due to the emergent, epidemic setting that led to the selection of a cluster-randomized phase 3 study design under field conditions